Detection of movement intention from neural signals combined with assistive technologies
may be used for effective neurofeedback in rehabilitation. In order to promote plasticity, a
causal relation between intended actions (detected for example from the EEG) and the
corresponding feedback should be established. This requires reliable detection of motor
intentions. In this study, we propose a method to detect movements from EEG with limited
latency. In a self-paced asynchronous BCI paradigm, the initial negative phase of the …

Detection of motor intention with short latency from scalp electroencephalography (EEG) is
essential for the development of brain-computer interface (BCI) systems for
neuromodulation. This latency determines the temporal association between motor intention
and the triggered afferent neurofeedback. In this study, we compared two typical
experimental paradigms for the detection of movement intention from EEG. A template-
matching algorithm was used to detect movement-related cortical potentials (MRCPs) in …